def test_coercion():
assert dt.Date().into("2004-05-05 00:00:00") == datetime(
year=2004, month=5, day=5, tzinfo=timezone.utc)
assert dt.Date().into("2019-11-16T08:00:00.000+10:00") == datetime(
year=2019, month=11, day=15, hour=22, tzinfo=timezone.utc)
assert dt.Date().into(datetime(year=2004, month=5,
day=5)) == datetime(year=2004,
month=5,
day=5,
tzinfo=timezone.utc)
assert dt.Array(items=dt.Date()).into(
["2004-05-05 00:00:00", "2019-11-16T08:00:00.000+10:00"]) == [
datetime(year=2004, month=5, day=5, tzinfo=timezone.utc),
datetime(year=2019, month=11, day=15, hour=22,
tzinfo=timezone.utc),
]
assert dt.Long().into("2004") == 2004
assert dt.Array(items=dt.Long()).into(["2004", "2005"]) == [2004, 2005]
assert dt.Double().into("3.14159") == 3.14159
assert dt.Array(items=dt.Double()).into(["3.14159",
"3.12"]) == [3.14159, 3.12]
assert dt.Boolean().into("true") is True
assert dt.Array(items=dt.Boolean()).into(["true",
"false"]) == [True, False]
with pytest.raises(ValueError):
dt.Array(items=dt.Long(), enum=[1, 2, 3]).into([1, 2, 4])
def test_deserialize_long_with_format():
assert dt.deserialize("""{ "type": "Long", "unit": null }""") == dt.Long(
unit=None)
assert dt.deserialize("""{ "type": "Long", "unit": "ms" }""") == dt.Long(
unit="ms")
assert dt.deserialize("""{ "type": "Long", "unit": "" }""") == dt.Long(
unit=None)
with pytest.raises(Exception):
assert dt.deserialize("""{ "type": "Long", "unit": 99 }""")
def test_simple_type_decoding():
assert dt.deserialize('"Boolean"') == dt.Boolean()
assert dt.deserialize('"Double"') == dt.Double()
assert dt.deserialize('"Long"') == dt.Long()
assert dt.deserialize('"String"') == dt.String()
assert dt.deserialize("Boolean") == dt.Boolean()
assert dt.deserialize("Double") == dt.Double()
assert dt.deserialize("Long") == dt.Long()
assert dt.deserialize("String") == dt.String()
def test_serialize_simple_types():
assert dt.serialize(dt.Boolean()) == """{"type": "Boolean"}"""
assert dt.serialize(
dt.String()) == """{"type": "String", "format": null}"""
assert (dt.serialize(dt.String(format=dt.StringSubtypeFormat.EMAIL)) ==
"""{"type": "String", "format": "Email"}""")
assert dt.serialize(dt.Double()) == """{"type": "Double", "unit": null}"""
assert (dt.serialize(dt.Double(
unit="inches")) == """{"type": "Double", "unit": "inches"}""")
assert dt.serialize(dt.Long()) == """{"type": "Long", "unit": null}"""
assert (dt.serialize(
dt.Long(unit="inches")) == """{"type": "Long", "unit": "inches"}""")
def test_simple_representation():
# Boolean
SimpleBoolean = dt.Boolean()
assert SimpleBoolean.is_simple
assert SimpleBoolean.into_simple() == "Boolean"
# Long
SimpleLong = dt.Long()
assert SimpleLong.is_simple
assert SimpleLong.into_simple() == "Long"
ComplexLong = dt.Long(unit="m/sec")
assert not ComplexLong.is_simple
# Double
SimpleDouble = dt.Double()
assert SimpleDouble.is_simple
assert SimpleDouble.into_simple() == "Double"
# String
SimpleString = dt.String()
assert SimpleString.is_simple
assert SimpleString.into_simple() == "String"
ComplexString = dt.String(format=dt.StringSubtypeFormat.EMAIL)
assert not ComplexString.is_simple
assert ComplexString.into_simple() is None
# Date
SimpleDate = dt.Date()
assert SimpleDate.is_simple
assert SimpleDate.into_simple() == "Date"
Array_ = dt.Array(
items=dt.String(format=dt.StringSubtypeFormat.EMAIL),
enum=["*****@*****.**", "*****@*****.**"],
)
assert not Array_.is_simple
assert Array_.into_simple() is None
Enum = dt.Enumeration(items=dt.Boolean(), enum=[True])
assert not Enum.is_simple
assert Enum.into_simple() is None
def test_deserialize_complex_type_decoding():
assert dt.deserialize("""{ "type": "Boolean" }""") == dt.Boolean()
assert dt.deserialize("""{ "type": "Double" }""") == dt.Double()
assert dt.deserialize("""{ "type": "Long" }""") == dt.Long()
assert dt.deserialize("""{ "type": "String" }""") == dt.String()
def properties():
now = datetime.now()
props = [
ModelProperty(
name="id",
display_name="ID",
data_type=dt.String(),
description="User ID",
required=True,
created_at=now,
updated_at=now,
),
ModelProperty(
name="name",
display_name="Name",
data_type=dt.String(),
description="Name",
required=True,
created_at=now,
updated_at=now,
),
ModelProperty(
name="age",
display_name="Age",
data_type=dt.Long(),
description="Age in years",
required=True,
created_at=now,
updated_at=now,
),
ModelProperty(
name="height",
display_name="Height",
data_type=dt.Double(unit="inches"),
description="Height in inches",
required=True,
created_at=now,
updated_at=now,
),
ModelProperty(
name="sex",
display_name="Sex",
data_type=dt.Enumeration(items=dt.String(), enum=["M", "F"]),
description="Sex",
required=True,
created_at=now,
updated_at=now,
),
ModelProperty(
name="salutation",
display_name="Salutation",
data_type=dt.Array(
items=dt.String(), enum=["Mr.", "Mrs.", "Ms.", "Dr.", "Esq."]
),
description="Salutation",
required=False,
created_at=now,
updated_at=now,
),
ModelProperty(
name="email",
display_name="Email",
data_type=dt.String(format=dt.StringSubtypeFormat.EMAIL),
description="Email address",
required=False,
created_at=now,
updated_at=now,
),
ModelProperty(
name="url",
display_name="URL",
data_type=dt.String(format=dt.StringSubtypeFormat.URL),
description="URL",
required=False,
created_at=now,
updated_at=now,
),
ModelProperty(
name="favorite_numbers",
display_name="Favorite numbers",
data_type=dt.Long(),
description="Favorite numbers",
required=False,
created_at=now,
updated_at=now,
),
ModelProperty(
name="favorite_color",
display_name="Favorite color",
data_type=dt.Enumeration(items=dt.String(), enum=["red", "green", "blue"]),
description="Favorite color",
required=False,
created_at=now,
updated_at=now,
),
]
return props
def test_record_value_serialization(s3, config, read_csv, metadata_key, partitioned_db):
s3.create_bucket(Bucket=config.s3_bucket)
patient = partitioned_db.create_model("patient", "Patient")
partitioned_db.update_properties(
patient,
ModelProperty(
name="string",
display_name="String",
data_type=dt.String(),
model_title=True,
),
ModelProperty(name="boolean", display_name="Boolean", data_type=dt.Boolean()),
ModelProperty(name="long", display_name="Long", data_type=dt.Long()),
ModelProperty(name="double", display_name="Double", data_type=dt.Double()),
ModelProperty(name="date", display_name="Date", data_type=dt.Date()),
ModelProperty(name="optional", display_name="Optional", data_type=dt.String()),
ModelProperty(
name="string_array",
display_name="String Array",
data_type=dt.Array(items=dt.String()),
),
ModelProperty(
name="boolean_array",
display_name="Boolean Array",
data_type=dt.Array(items=dt.Boolean()),
),
ModelProperty(
name="long_array",
display_name="Long Array",
data_type=dt.Array(items=dt.Long()),
),
ModelProperty(
name="double_array",
display_name="Double Array",
data_type=dt.Array(items=dt.Double()),
),
ModelProperty(
name="date_array",
display_name="Date Array",
data_type=dt.Array(items=dt.Date()),
),
)
record = partitioned_db.create_records(
patient,
[
{
"string": 'tricky"char,acter"string',
"boolean": True,
"long": 12345,
"double": 3.14159,
"date": datetime.datetime(year=2004, month=5, day=5),
"optional": None,
"string_array": ["red", "green", "semi;colon"],
"boolean_array": [True, False],
"long_array": [1, 2, 3],
"double_array": [1.1, 2.2, 3.3],
"date_array": [
datetime.datetime(year=2004, month=5, day=5),
datetime.datetime(year=2014, month=5, day=16),
],
}
],
)[0]
publish_dataset(partitioned_db, s3, config, file_manifests=[])
patient_csv = read_csv(metadata_key("records/patient.csv"))
assert patient_csv.rows == [
OrderedDict(
{
"id": str(record.id),
"string": 'tricky"char,acter"string',
"boolean": "true",
"long": "12345",
"double": "3.14159",
"date": "2004-05-05T00:00:00",
"optional": "",
"string_array": "red;green;semi_colon",
"boolean_array": "true;false",
"long_array": "1;2;3",
"double_array": "1.1;2.2;3.3",
"date_array": "2004-05-05T00:00:00;2014-05-16T00:00:00",
}
)
]